· ai
[Paper] Advancing Language Models for Code-related Tasks
Recent advances in language models (LMs) have driven significant progress in various software engineering tasks. However, existing LMs still struggle with compl...
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- · ai
What is a Vector Space in Machine Learning? (With Math and Intuition)
Machine‑Learning and Vector Spaces In machine learning, data is often represented in vector spaces so that mathematical operations such as addition combination...
- · ai
[Paper] Phasor Agents: Oscillatory Graphs with Three-Factor Plasticity and Sleep-Staged Learning
Phasor Agents are dynamical systems whose internal state is a Phasor Graph: a weighted graph of coupled Stuart-Landau oscillators. A Stuart-Landau oscillator is...
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[Paper] Embedding Autonomous Agents in Resource-Constrained Robotic Platforms
Many embedded devices operate under resource constraints and in dynamic environments, requiring local decision-making capabilities. Enabling devices to make ind...
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[Paper] Lightweight Test-Time Adaptation for EMG-Based Gesture Recognition
Reliable long-term decoding of surface electromyography (EMG) is hindered by signal drift caused by electrode shifts, muscle fatigue, and posture changes. While...
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[Paper] Robust Physics Discovery from Highly Corrupted Data: A PINN Framework Applied to the Nonlinear Schrödinger Equation
We demonstrate a deep learning framework capable of recovering physical parameters from the Nonlinear Schrodinger Equation (NLSE) under severe noise conditions....
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[Paper] Agentic Rubrics as Contextual Verifiers for SWE Agents
Verification is critical for improving agents: it provides the reward signal for Reinforcement Learning and enables inference-time gains through Test-Time Scali...
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[Paper] Agent Drift: Quantifying Behavioral Degradation in Multi-Agent LLM Systems Over Extended Interactions
Multi-agent Large Language Model (LLM) systems have emerged as powerful architectures for complex task decomposition and collaborative problem-solving. However,...
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[Paper] Clinical Data Goes MEDS? Let's OWL make sense of it
The application of machine learning on healthcare data is often hindered by the lack of standardized and semantically explicit representation, leading to limite...
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[Paper] Scanner-Induced Domain Shifts Undermine the Robustness of Pathology Foundation Models
Pathology foundation models (PFMs) have become central to computational pathology, aiming to offer general encoders for feature extraction from whole-slide imag...
- · ai
[Paper] FLEx: Language Modeling with Few-shot Language Explanations
Language models have become effective at a wide range of tasks, from math problem solving to open-domain question answering. However, they still make mistakes, ...
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[Paper] Klear: Unified Multi-Task Audio-Video Joint Generation
Audio-video joint generation has progressed rapidly, yet substantial challenges still remain. Non-commercial approaches still suffer audio-visual asynchrony, po...